State Space Feedforward and Feedback Structures for Blind Source Recovery

This paper presents two separate structures for the blind source recovery (BSR) of stochastically independent signal sources. We hypothesize linear state space models for both the mixing environment and the demixing (i.e. recovering) adaptive network. Separate algorithms for adaptive estimation of parameters for the feedforward and feedback recovering networks have been derived. Auxillay conditions for the convergence of these algorithms have also been derived and discussed. Simulation examples have been included to compare the results for both algorithms for an IIR mixing environment. Conclusive remarks about effectiveness of these techniques in various practical problems have also been included.